Machine Learning Engineer

5+ years of experience as a Data Scientist, ideally in fast-paced or high-growth environments

Proficiency in SQL and experience working with large-scale data systems (e.g., Redshift, BigQuery, Snowflake).

Strong analytical and statistical skills; fluency in Python or R.

Experience with machine learning libraries (e.g., scikit-learn, XGBoost) and data visualization tools (e.g., Tableau, Looker, Plotly).

Solid understanding of experimental design, hypothesis testing, and causal inference.

Ability to distill complex data problems into clear, actionable insights.

Lead high-impact projects: Design and deliver end-to-end data science solutions that support product innovation and business strategy.

Uncover insights: Analyze large, complex datasets to identify trends, surface opportunities, and influence key decisions.

Build models: Develop and deploy predictive and prescriptive models using machine learning and statistical techniques.

Enable experimentation: Design A/B tests and causal inference studies to help teams learn quickly and make informed choices.

Collaborate cross-functionally: Work closely with product managers, engineers, and business leaders to understand goals and deliver data-driven solutions.

Promote data fluency: Build dashboards, tools, and frameworks to enable self-service analytics and scale your impact across teams.